As the date rates and bandwidths of communication systems scale up, the cost and power consumption of highprecision (e.g., 8-12 bits) analog-to-digital converters (ADCs) become pro...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
We present a new approach for simplifying polygonal objects. Our method is general in that it works on models that contain both non-manifold geometry and surface attributes. It is...
Segmentation of continuous audio is important for speaker indexing. The reliability of models in speaker indexing depends much on segmentation. Commonly used method is based on th...
In this work we consider the task of relaxing the i.i.d assumption in online pattern recognition (or classification), aiming to make existing learning algorithms applicable to a ...